%0 Journal Article %J EBioMedicine %D 2021 %T Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium. %A Lin, Bridget M %A Grinde, Kelsey E %A Brody, Jennifer A %A Breeze, Charles E %A Raffield, Laura M %A Mychaleckyj, Josyf C %A Thornton, Timothy A %A Perry, James A %A Baier, Leslie J %A de Las Fuentes, Lisa %A Guo, Xiuqing %A Heavner, Benjamin D %A Hanson, Robert L %A Hung, Yi-Jen %A Qian, Huijun %A Hsiung, Chao A %A Hwang, Shih-Jen %A Irvin, Margaret R %A Jain, Deepti %A Kelly, Tanika N %A Kobes, Sayuko %A Lange, Leslie %A Lash, James P %A Li, Yun %A Liu, Xiaoming %A Mi, Xuenan %A Musani, Solomon K %A Papanicolaou, George J %A Parsa, Afshin %A Reiner, Alex P %A Salimi, Shabnam %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Taylor, Kent D %A Smith, Albert V %A Smith, Jennifer A %A Tin, Adrienne %A Vaidya, Dhananjay %A Wallace, Robert B %A Yamamoto, Kenichi %A Sakaue, Saori %A Matsuda, Koichi %A Kamatani, Yoichiro %A Momozawa, Yukihide %A Yanek, Lisa R %A Young, Betsi A %A Zhao, Wei %A Okada, Yukinori %A Abecasis, Gonzalo %A Psaty, Bruce M %A Arnett, Donna K %A Boerwinkle, Eric %A Cai, Jianwen %A Yii-Der Chen, Ida %A Correa, Adolfo %A Cupples, L Adrienne %A He, Jiang %A Kardia, Sharon Lr %A Kooperberg, Charles %A Mathias, Rasika A %A Mitchell, Braxton D %A Nickerson, Deborah A %A Turner, Steve T %A Vasan, Ramachandran S %A Rotter, Jerome I %A Levy, Daniel %A Kramer, Holly J %A Köttgen, Anna %A Rich, Stephen S %A Lin, Dan-Yu %A Browning, Sharon R %A Franceschini, Nora %X

BACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.

METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.

FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.

INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

%B EBioMedicine %V 63 %P 103157 %8 2021 Jan %G eng %R 10.1016/j.ebiom.2020.103157 %0 Journal Article %J Hypertension %D 2022 %T Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. %A Kelly, Tanika N %A Sun, Xiao %A He, Karen Y %A Brown, Michael R %A Taliun, Sarah A Gagliano %A Hellwege, Jacklyn N %A Irvin, Marguerite R %A Mi, Xuenan %A Brody, Jennifer A %A Franceschini, Nora %A Guo, Xiuqing %A Hwang, Shih-Jen %A de Vries, Paul S %A Gao, Yan %A Moscati, Arden %A Nadkarni, Girish N %A Yanek, Lisa R %A Elfassy, Tali %A Smith, Jennifer A %A Chung, Ren-Hua %A Beitelshees, Amber L %A Patki, Amit %A Aslibekyan, Stella %A Blobner, Brandon M %A Peralta, Juan M %A Assimes, Themistocles L %A Palmas, Walter R %A Liu, Chunyu %A Bress, Adam P %A Huang, Zhijie %A Becker, Lewis C %A Hwa, Chii-Min %A O'Connell, Jeffrey R %A Carlson, Jenna C %A Warren, Helen R %A Das, Sayantan %A Giri, Ayush %A Martin, Lisa W %A Craig Johnson, W %A Fox, Ervin R %A Bottinger, Erwin P %A Razavi, Alexander C %A Vaidya, Dhananjay %A Chuang, Lee-Ming %A Chang, Yen-Pei C %A Naseri, Take %A Jain, Deepti %A Kang, Hyun Min %A Hung, Adriana M %A Srinivasasainagendra, Vinodh %A Snively, Beverly M %A Gu, Dongfeng %A Montasser, May E %A Reupena, Muagututi'a Sefuiva %A Heavner, Benjamin D %A LeFaive, Jonathon %A Hixson, James E %A Rice, Kenneth M %A Wang, Fei Fei %A Nielsen, Jonas B %A Huang, Jianfeng %A Khan, Alyna T %A Zhou, Wei %A Nierenberg, Jovia L %A Laurie, Cathy C %A Armstrong, Nicole D %A Shi, Mengyao %A Pan, Yang %A Stilp, Adrienne M %A Emery, Leslie %A Wong, Quenna %A Hawley, Nicola L %A Minster, Ryan L %A Curran, Joanne E %A Munroe, Patricia B %A Weeks, Daniel E %A North, Kari E %A Tracy, Russell P %A Kenny, Eimear E %A Shimbo, Daichi %A Chakravarti, Aravinda %A Rich, Stephen S %A Reiner, Alex P %A Blangero, John %A Redline, Susan %A Mitchell, Braxton D %A Rao, Dabeeru C %A Ida Chen, Yii-Der %A Kardia, Sharon L R %A Kaplan, Robert C %A Mathias, Rasika A %A He, Jiang %A Psaty, Bruce M %A Fornage, Myriam %A Loos, Ruth J F %A Correa, Adolfo %A Boerwinkle, Eric %A Rotter, Jerome I %A Kooperberg, Charles %A Edwards, Todd L %A Abecasis, Goncalo R %A Zhu, Xiaofeng %A Levy, Daniel %A Arnett, Donna K %A Morrison, Alanna C %X

BACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.

METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.

RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5×10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99×10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18×10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28×10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1×10 and <1×10, respectively).

DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

%B Hypertension %P 101161HYPERTENSIONAHA12219324 %8 2022 Jun 02 %G eng %R 10.1161/HYPERTENSIONAHA.122.19324 %0 Journal Article %J Am J Hum Genet %D 2022 %T Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. %A Hindy, George %A Dornbos, Peter %A Chaffin, Mark D %A Liu, Dajiang J %A Wang, Minxian %A Selvaraj, Margaret Sunitha %A Zhang, David %A Park, Joseph %A Aguilar-Salinas, Carlos A %A Antonacci-Fulton, Lucinda %A Ardissino, Diego %A Arnett, Donna K %A Aslibekyan, Stella %A Atzmon, Gil %A Ballantyne, Christie M %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Becker, Lewis C %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Bown, Matthew J %A Brody, Jennifer A %A Broome, Jai G %A Burtt, Noel P %A Cade, Brian E %A Centeno-Cruz, Federico %A Chan, Edmund %A Chang, Yi-Cheng %A Chen, Yii-der I %A Cheng, Ching-Yu %A Choi, Won Jung %A Chowdhury, Rajiv %A Contreras-Cubas, Cecilia %A Córdova, Emilio J %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Danesh, John %A de Vries, Paul S %A DeFronzo, Ralph A %A Doddapaneni, Harsha %A Duggirala, Ravindranath %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Florez, Jose C %A Fornage, Myriam %A Freedman, Barry I %A Fuster, Valentin %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Germer, Soren %A Gibbs, Richard A %A Gieger, Christian %A Glaser, Benjamin %A Gonzalez, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Graff, Mariaelisa %A Graham, Sarah E %A Grarup, Niels %A Groop, Leif C %A Guo, Xiuqing %A Gupta, Namrata %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A He, Jiang %A Heard-Costa, Nancy L %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Irvin, Marguerite R %A Islas-Andrade, Sergio %A Jarvik, Gail P %A Kang, Hyun Min %A Kardia, Sharon L R %A Kelly, Tanika %A Kenny, Eimear E %A Khan, Alyna T %A Kim, Bong-Jo %A Kim, Ryan W %A Kim, Young Jin %A Koistinen, Heikki A %A Kooperberg, Charles %A Kuusisto, Johanna %A Kwak, Soo Heon %A Laakso, Markku %A Lange, Leslie A %A Lee, Jiwon %A Lee, Juyoung %A Lee, Seonwook %A Lehman, Donna M %A Lemaitre, Rozenn N %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lubitz, Steven A %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martin, Lisa Warsinger %A Martínez-Hernández, Angélica %A Mathias, Rasika A %A McGarvey, Stephen T %A McPherson, Ruth %A Meigs, James B %A Meitinger, Thomas %A Melander, Olle %A Mendoza-Caamal, Elvia %A Metcalf, Ginger A %A Mi, Xuenan %A Mohlke, Karen L %A Montasser, May E %A Moon, Jee-Young %A Moreno-Macias, Hortensia %A Morrison, Alanna C %A Muzny, Donna M %A Nelson, Sarah C %A Nilsson, Peter M %A O'Connell, Jeffrey R %A Orho-Melander, Marju %A Orozco, Lorena %A Palmer, Colin N A %A Palmer, Nicholette D %A Park, Cheol Joo %A Park, Kyong Soo %A Pedersen, Oluf %A Peralta, Juan M %A Peyser, Patricia A %A Post, Wendy S %A Preuss, Michael %A Psaty, Bruce M %A Qi, Qibin %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Samani, Nilesh %A Schunkert, Heribert %A Schurmann, Claudia %A Seo, Daekwan %A Seo, Jeong-Sun %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Stilp, Adrienne M %A Tai, E Shyong %A Tam, Claudia H T %A Taylor, Kent D %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tsai, Michael Y %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A van Dam, Rob M %A Vasan, Ramachandran S %A Viaud Martinez, Karine A %A Wang, Fei Fei %A Wang, Xuzhi %A Watkins, Hugh %A Weeks, Daniel E %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Yanek, Lisa R %A Kathiresan, Sekar %A Rader, Daniel J %A Rotter, Jerome I %A Boehnke, Michael %A McCarthy, Mark I %A Willer, Cristen J %A Natarajan, Pradeep %A Flannick, Jason A %A Khera, Amit V %A Peloso, Gina M %K Alleles %K Blood Glucose %K Case-Control Studies %K Computational Biology %K Databases, Genetic %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Predisposition to Disease %K Genetic Variation %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Lipid Metabolism %K Lipids %K Liver %K Molecular Sequence Annotation %K Multifactorial Inheritance %K Open Reading Frames %K Phenotype %K Polymorphism, Single Nucleotide %X

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

%B Am J Hum Genet %V 109 %P 81-96 %8 2022 01 06 %G eng %N 1 %R 10.1016/j.ajhg.2021.11.021 %0 Journal Article %J Hum Mol Genet %D 2022 %T Whole-Exome Sequencing Study Identifies Four Novel Gene Loci Associated with Diabetic Kidney Disease. %A Pan, Yang %A Sun, Xiao %A Mi, Xuenan %A Huang, Zhijie %A Hsu, Yenchih %A Hixson, James E %A Munzy, Donna %A Metcalf, Ginger %A Franceschini, Nora %A Tin, Adrienne %A Köttgen, Anna %A Francis, Michael %A Brody, Jennifer A %A Kestenbaum, Bryan %A Sitlani, Colleen M %A Mychaleckyj, Josyf C %A Kramer, Holly %A Lange, Leslie A %A Guo, Xiuqing %A Hwang, Shih-Jen %A Irvin, Marguerite R %A Smith, Jennifer A %A Yanek, Lisa R %A Vaidya, Dhananjay %A Chen, Yii-Der Ida %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Hou, Lifang %A Mathias, Rasika A %A Mitchell, Braxton D %A Peyser, Patricia A %A Kardia, Sharon L R %A Arnett, Donna K %A Correa, Adolfo %A Raffield, Laura M %A Vasan, Ramachandran S %A Cupple, L Adrienne %A Levy, Daniel %A Kaplan, Robert C %A North, Kari E %A Rotter, Jerome I %A Kooperberg, Charles %A Reiner, Alexander P %A Psaty, Bruce M %A Tracy, Russell P %A Gibbs, Richard A %A Morrison, Alanna C %A Feldman, Harold %A Boerwinkle, Eric %A He, Jiang %A Kelly, Tanika N %X

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease (CKD) and diabetes. Our two-stage whole-exome sequencing study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort (CRIC) and Atherosclerosis Risk in Communities (ARIC) studies (stage-1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine (TOPMed) participants (stage-2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex, and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test (SKAT-O) implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds (95% confidence interval: 33.6, 1105) of DKD compared with non-carriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% confidence interval: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

%B Hum Mol Genet %8 2022 Nov 29 %G eng %R 10.1093/hmg/ddac290